Lead Machine Learning Engineer (MLE) at Quadric

Vancouver, British Columbia, Canada

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Insurance, Technology, FinTechIndustries

Requirements

Expertise in designing and implementing real-time learning systems that evolve from bot interactions, document processing, and customer feedback
Ability to build feedback loop architectures and models integrating signals from broker activities and customer interactions to improve model accuracy, reliability, and capabilities
Proficiency in conducting advanced statistical analysis, exploring complex datasets, uncovering business opportunities, and performing market research through data
Experience partnering with Product, Engineering, Sales, Marketing, and Leadership stakeholders to translate business questions into analytical frameworks and data-driven solutions
Skills in building predictive models, forecasting, impact analysis, statistical models, and the surrounding systems to support business decision-making
Capability to identify new analytical opportunities, research emerging methodologies, leverage AI tools, and drive data science best practices
End-to-end ownership: Ability to take models from research to production and maintain them
Experience working closely with Data Engineers, ML Engineers, AI Engineers, ML Ops, Software Engineers, and Data Scientists to integrate data insights, engineering best practices, and tech review
Ownership of the ML model lifecycle

Responsibilities

Drive the evolution of the continuous learning system behind AI and analytics
Establish core infrastructure for the learning flywheel
Conduct advanced statistical analysis and explore complex datasets to uncover business opportunities
Perform market research through data
Partner with stakeholders (Product, Engineering, Sales, Marketing, Leadership) to translate business questions into analytical frameworks and data-driven solutions
Build predictive models, forecasting, impact analysis, statistical models, and supporting systems for business decision-making
Identify new analytical opportunities, research emerging methodologies, leverage AI tools, and drive data science best practices
Take end-to-end ownership of models from research to production and maintenance
Collaborate with Data Engineers, ML Engineers, AI Engineers, ML Ops, Software Engineers, and Data Scientists to deliver production systems and analysis
Own the ML model lifecycle

Skills

Machine Learning

Python

Data Science

Automation

Cloud Computing

Quadric

Simplifies SoC design for machine learning

About Quadric

Quadric focuses on simplifying the design and programming of System on Chips (SoCs) specifically for machine learning applications. Their main product is the Chimera, a General-Purpose Neural Processing Unit (GPNPU) that combines matrix and vector operations with scalar control code in a single execution pipeline. This design allows developers to avoid splitting application code across different processors, making the development process more efficient. Quadric serves clients in the semiconductor industry, including SoC developers and manufacturers, who need to improve their machine learning capabilities. Unlike competitors, Quadric offers a comprehensive solution that includes both hardware and software tools, such as the Chimera LLVM C Compiler and the Chimera Instruction Set Simulator, enabling developers to design, simulate, and deploy their applications effectively. The goal of Quadric is to enhance the performance and ease of development for machine learning applications on SoCs.

Burlingame, CaliforniaHeadquarters

2017Year Founded

$42.1MTotal Funding

DEBTCompany Stage

Hardware, Enterprise Software, AI & Machine LearningIndustries

51-200Employees

Benefits

Health Insurance

Dental Insurance

Vision Insurance

401(k) Retirement Plan

Company Equity

Risks

Increased competition from established semiconductor companies threatens market share.

Rapid AI advancements may outpace Quadric's current product offerings.

Potential IP disputes could lead to costly legal battles.

Differentiation

Chimera GPNPU integrates matrix, vector, and scalar operations in one pipeline.

Quadric's GPNPU runs C code, enhancing versatility for neural network operations.

Quadric offers a unified architecture for ML inference and C++ processing.

Upsides

Quadric's Series B funding boosts expansion of engineering and commercial teams.

Partnership with Ams Osram enhances smart sensing solutions for edge applications.

Quadric Developer Studio simplifies AI and ML application development.

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